Self-Organizing Networks (SONs) have an important role in the development of the next generation of mobile networks by introducing automated schemes to allow base stations to be added and removed from the network without the need for human intervention to reorganize the network by updating neighbor lists, frequency allocations and other interactions between the base stations. The term “cell” as used herein means the area associated with each base station in which that base station is the primary means of communication between any mobile terminals currently in that area and the fixed “backhaul” infrastructure. In practice, the areas within which the individual base stations can make reliable contact with mobile terminals generally overlap to some extent, making it possible to hand over a mobile terminal from one base station to another without interruption. In a self-organizing network it is also necessary for each base station to be able to detect the presence of its neighbors, which may be done by direct wireless communication or through a supervisory system.
The terms “macrocell” “microcell” and “femtocell” are used herein in a relative sense to describe cells, and their associated base stations, with different sizes of areas of coverage. Typically a macrocell covers a range of a few kilometers, and a microcell covers a smaller area of where infill of the macrocell network is required either because of high traffic levels or difficulties in coverage by the macrocell network because of obstructions—a typical location is a city street. Femtocells are intended for very small coverage areas, typically indoors, and are useful both at sites with difficulties with reception and where high data rates are required. It is expected that future cellular networks will be heterogeneous networks (HetNets), i.e., a mix of macro-cells for ubiquitous user experience and small cells or femto access points (FAPs) for high data rate transmission.
Cell outage detection is one of the main functions required in a self-healing mechanism. Most outage detection algorithms are focused on macro-cells rather than small cells. Most previous outage detection algorithms are not suitable for such networks due to the dense deployment nature of FAPs in the HetNets, as compared to the macro only deployments. Furthermore, there is high possibility of having sparse user statistics in small cells, since they usually support very few users as compared to macro-cells. Macro cells tend to be associated with permanent base stations. It is also more common for smaller cells to be added and removed from the network, as they are usually under the control of individual users rather than the network operator, and the user may wish to power down the base station when he is not using it himself, or to take it to another location.
It is known to implement a distributed outage trigger mechanism and sequential hypothesis testing within a predefined cooperation range, by analyzing the Reference Signal Received Power (RSRP) statistics of the users within the cooperative range. The FAPs monitor their neighbors over the “X2” interface (Inter-eNodeB interface defined in 3GPP). These IP-based techniques are likely to result in network overload especially when, as is expected, many thousands of femtocells are deployed. Polling via X2 also generates additional network traffic, and suffers from the same reliability issues as centralized polling. Polling from a local Home Hub may be useful (especially in case where there are no neighbor Femto cells to report an outage) but is at risk of a common failure mode (hardware/power/backhaul) such that two or more neighboring cells may be affected by a common cause and thus none of them are able to report the outage.
Moreover, these systems do not take into account the possibility of devices going into sleep mode, so a FAP in idle/sleep mode will be mistakenly taken as an outage, which results in unnecessary compensation procedures, and more communications overhead.
“Femtocell Collaborative Outage Detection with Built in Sleeping mode recovery” (Abouelmaati et al: Lecture Notes of the Institute for Computer Sciences, Social informatics and Telecommunications Engineering, January 2015) describes a sleep recovery system in which FAPs report a sleep mode and then other femtocells process the data, replace the sleeping statistics, and then perform the Outage detection process. However, transitory but unplanned outages, or situations in which interference or other factors cause a sniffer to fail to detect a reference signal, may be mistakenly reported as outages.